Business Data Scientist, Google Customer Solutions Ads Finance

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  

Preferred qualifications:

• PHD in Economics, Statistics, or a related field
• 6 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

In this role, you will have an opportunity to directly shape the incentives and future of our business. You will contribute to over 20 distinct programs and continuously develop your data science skills. You will also explore time series analysis, examine business drivers, and help build the foundational infrastructure for revenue analytics and research.

The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Develop statistical hypotheses and build predictive models.
• Build and work with complex datasets effectively. Create and maintain analytical solutions using SQL/ plx, Python or R.
• Work with business teams to influence program design and explain goal setting and investigative methodologies. 
• Translate complexity and explain sophisticated analysis and methodologies to both engineering and business stakeholders.